also in machines: information overload. To work efficiently in a variety of complex environments, animals and machines are equipped with an array of sensors, all of which are needed in one situation or another to assure survival of the animal or proper function of the machine. In any given situation, however, only a subset of the sensory input is needed, and it would be wasteful (and, in many cases, practically impossible) to process all sensory input at all times. Therefore, selection has to be made which sensors are relevant at a given time, and only information provided by those is allowed access to central processing resources. Frequently, even the input stream from one sensor may be overwhelmingly rich. For instance, all visual input to the human brain1 is provided by about 106 retinal ganglion cells per eye. Assuming a maximal firing rate of these neurons of about 100 Hz results in a channel capacity of 100 Mb/s per eye. Indeed, analyses of spike train statistics of visual input to the brain in primates [1], carnivores [2], and insects [3] confirm that the rate of the transmitted information is within an order of magnitude of the channel capacity. This torrent of information cannot be, and does not have to be, processed in detail. Instead, only a fraction of the instantaneously available information is selected for detailed processing while the remainder is discarded.